B
binomial distribution
7.3 Using the Central Limit Theorem,
9.3 Distribution Needed for Hypothesis Testing
binomial probability distribution
4.3 Binomial Distribution (Optional)
bivariate
Introduction
Blinding
1.4 Experimental Design and Ethics
Box plots
2.4 Box Plots
box-and-whisker plots
2.4 Box Plots
box-whisker plots
2.4 Box Plots
C
categorical data
1.2 Data, Sampling, and Variation in Data and Sampling
Categorical variables
1.1 Definitions of Statistics, Probability, and Key Terms
central limit theorem
Introduction,
7.1 The Central Limit Theorem for Sample Means (Averages),
7.3 Using the Central Limit Theorem
central limit theorem for means
7.1 The Central Limit Theorem for Sample Means (Averages)
central limit theorem for sums
7.2 The Central Limit Theorem for Sums (Optional)
chi-square distribution
11.1 Facts About the Chi-Square Distribution
coefficient of determination
12.2 The Regression Equation
complement
3.1 Terminology
confidence level
8.1 A Single Population Mean Using the Normal Distribution,
8.3 A Population Proportion
continuity correction factor
7.3 Using the Central Limit Theorem
continuous random variable
5.3 The Exponential Distribution (Optional)
control group
1.4 Experimental Design and Ethics
critical value
6.2 Using the Normal Distribution
cumulative distribution function
5.1 Continuous Probability Functions
cumulative distribution function (CDF)
5.3 The Exponential Distribution (Optional)
Cumulative relative frequency
1.3 Frequency, Frequency Tables, and Levels of Measurement
D
data
1.1 Definitions of Statistics, Probability, and Key Terms,
1.1 Definitions of Statistics, Probability, and Key Terms
degrees of freedom (df)
10.1 Two Population Means with Unknown Standard Deviations
descriptive statistics
1.1 Definitions of Statistics, Probability, and Key Terms
double-blind experiment
1.4 Experimental Design and Ethics
E
error bound
8.3 A Population Proportion
error bound for a population mean
8.1 A Single Population Mean Using the Normal Distribution
expected value
4.2 Mean or Expected Value and Standard Deviation
expected values
11.2 Goodness-of-Fit Test
Experimental Probability of Event A
3.1 Terminology
exponential distribution
5.3 The Exponential Distribution (Optional),
7.3 Using the Central Limit Theorem
F
F distribution
13.2 The F Distribution and the F Ratio
first quartile
2.3 Measures of the Location of the Data
G
geometric distribution
4.4 Geometric Distribution (Optional)
geometric experiment
4.4 Geometric Distribution (Optional)
H
hypergeometric experiment
4 Chapter Review
hypergeometric probability
4.5 Hypergeometric Distribution (Optional)
hypotheses
9.1 Null and Alternative Hypotheses
hypothesis testing.
Introduction
I
independent
3.3 Two Basic Rules of Probability
independent events
3.2 Independent and Mutually Exclusive Events
informed consent
1.4 Experimental Design and Ethics
Institutional Review Boards (IRB)
1.4 Experimental Design and Ethics
interquartile range
2.3 Measures of the Location of the Data
interval scale
1.3 Frequency, Frequency Tables, and Levels of Measurement
L
law of large numbers
7.3 Using the Central Limit Theorem
level of measurement
1.3 Frequency, Frequency Tables, and Levels of Measurement
level of significance of the test
9.4 Rare Events, the Sample, and the Decision and Conclusion
lurking variables
1.4 Experimental Design and Ethics
M
margin of error
Introduction
mathematical models
1.1 Definitions of Statistics, Probability, and Key Terms
mean
1.1 Definitions of Statistics, Probability, and Key Terms,
2.5 Measures of the Center of the Data,
4.2 Mean or Expected Value and Standard Deviation,
Introduction,
7.1 The Central Limit Theorem for Sample Means (Averages),
7.3 Using the Central Limit Theorem
multivariate
Introduction
mutually exclusive
3.2 Independent and Mutually Exclusive Events,
3.3 Two Basic Rules of Probability
N
normal distribution
8.2 A Single Population Mean Using the Student's t-Distribution,
9.3 Distribution Needed for Hypothesis Testing
normally distributed
7.1 The Central Limit Theorem for Sample Means (Averages),
7.2 The Central Limit Theorem for Sums (Optional),
9.3 Distribution Needed for Hypothesis Testing
null hypothesis
9.1 Null and Alternative Hypotheses,
9.4 Rare Events, the Sample, and the Decision and Conclusion
Numerical variables
1.1 Definitions of Statistics, Probability, and Key Terms
O
observational studies
1.4 Experimental Design and Ethics
observed values
11.2 Goodness-of-Fit Test
P
p-value
9.4 Rare Events, the Sample, and the Decision and Conclusion,
9.5 Additional Information and Full Hypothesis Test Examples
paired data set
2.2 Histograms, Frequency Polygons, and Time Series Graphs
parameter
Introduction
percentiles
2.3 Measures of the Location of the Data
point estimate
Introduction
pooled proportion
10.3 Comparing Two Independent Population Proportions
population
1.1 Definitions of Statistics, Probability, and Key Terms,
1.2 Data, Sampling, and Variation in Data and Sampling
population variance
11.6 Test of a Single Variance
potential outlier
12.5 Outliers
probability density function
Introduction
probability distribution function
4.1 Probability Distribution Function (PDF) for a Discrete Random Variable
Q
Qualitative data
1.2 Data, Sampling, and Variation in Data and Sampling
quantitative continuous data
1.2 Data, Sampling, and Variation in Data and Sampling
Quantitative data
1.2 Data, Sampling, and Variation in Data and Sampling
quantitative discrete data
1.2 Data, Sampling, and Variation in Data and Sampling
R
random assignment
1.4 Experimental Design and Ethics
Random variable
10.1 Two Population Means with Unknown Standard Deviations,
10.2 Two Population Means with Known Standard Deviations
relative frequency
1.3 Frequency, Frequency Tables, and Levels of Measurement,
2.2 Histograms, Frequency Polygons, and Time Series Graphs
replacement
3.2 Independent and Mutually Exclusive Events
representative sample
1.1 Definitions of Statistics, Probability, and Key Terms
S
sampling distribution
2.5 Measures of the Center of the Data
sampling variability of a statistic
2.7 Measures of the Spread of the Data
simple random sample
9.3 Distribution Needed for Hypothesis Testing
standard deviation
2.7 Measures of the Spread of the Data,
8.2 A Single Population Mean Using the Student's t-Distribution,
9.3 Distribution Needed for Hypothesis Testing,
9.3 Distribution Needed for Hypothesis Testing,
9.4 Rare Events, the Sample, and the Decision and Conclusion,
10.1 Two Population Means with Unknown Standard Deviations
standard deviation of a discrete probability distribution
4.2 Mean or Expected Value and Standard Deviation
standard error
10.1 Two Population Means with Unknown Standard Deviations
standard error of the mean
7.1 The Central Limit Theorem for Sample Means (Averages)
Student's t-distribution
8.2 A Single Population Mean Using the Student's t-Distribution,
9.3 Distribution Needed for Hypothesis Testing,
9.3 Distribution Needed for Hypothesis Testing
sum of squared errors (SSE)
12.2 The Regression Equation
T
test for homogeneity
11.4 Test for Homogeneity
test of a single variance
11.6 Test of a Single Variance
test of independence
11.3 Test of Independence
Theoretical Probability of Event A
3.1 Terminology
tree diagram
3.5 Tree and Venn Diagrams
two-way table
3.4 Contingency Tables
Type I error
9.2 Outcomes and the Type I and Type II Errors,
9.4 Rare Events, the Sample, and the Decision and Conclusion
Type II error
9.2 Outcomes and the Type I and Type II Errors
U
unfair
3.1 Terminology
uniform distribution
7.3 Using the Central Limit Theorem
Use the following information to answer the next three exercises
3 Homework